Evidence map›Paper›PMID 42180666›Full record

ArticleChina CDC weekly2026

A Comprehensive Comparison of Transition Point Detection Methods for Monkeypox - Africa, 2024-2025.

Mengshou Wang, Zibin Yu, Ling Yin, Liu Hong

Abstract read
In one paragraph

Article in China CDC weekly, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mengshou WangSchool of Mathematics, Sun Yat-sen University, Guangzhou City, Guangdong Province, China.
Zibin YuSchool of Mathematics, Sun Yat-sen University, Guangzhou City, Guangdong Province, China.
Ling YinShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen City, Guangdong Province, China.
Liu HongSchool of Mathematics, Sun Yat-sen University, Guangzhou City, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Since May 2022, the global outbreak of mpox has presented a substantial public health challenge, with recent severe resurgences reported in several African countries, particularly in the Democratic Republic of the Congo (DRC). What is added by this report?: This study developed compartmental- and network-based models using epidemiological data from the DRC, a country that has experienced a recent major outbreak. The applicability of the four methods for transition point detection in mpox transmission was confirmed for the first time. The strengths and limitations of each approach were evaluated systematically and quantitatively. What are the implications for public health practice?: These findings provide theoretical guidance for identifying epidemic transition points in the mpox outbreak response and offer a reference for the rational allocation of public health resources during epidemics.

Indexed as

Epidemic controlEpidemic forecastingmpoxTransition point detection

Identifiers

PMID42180666
PMCPMC13191289

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.